Are you holding Master’s degree and ready to elevate your academic journey to the highest level? Uppsala University, Sweden, has announced a multiple fully funded PhD positions awaiting talented individuals like you. Don’t miss your chance to be part of our vibrant academic community. Explore the exciting PhD positions available and submit your application today!”
Candidates interested in fully funded PhD positions can check the details and may apply as soon as possible.
(01) Fully Funded PhD Position
PhD position summary/title:– Doctoral student in computational linguistics with a focus on criminal procedure lawDoctoral student in computational linguistics with a focus on criminal procedure law
The doctoral studies are conducted within the framework of the research environment “International Center for Evidence-Based Criminal Law (EB-CRIME)”, funded by the Swedish Research Council, the Knut and Alice Wallenberg Foundation and the Riksbank’s Jubilee Fund.
EB-CRIME is a constellation of 11 researchers specialized in nine different disciplines; law, psychology, sociology, information technology, genetics, medicine, chemistry, anthropology and digital forensics. The researchers collaborate in 6 sub-projects, all of which deal with commonly used types of evidence in criminal cases. The 6 sub-projects are: Oral statements, digital forensics, molecular diagnostics, forensic anthropology, forensic medicine and age assessments. The purpose of the research is to contribute to ‘best practice guidelines’ for practitioners such as forensics, coroners, police officers, prosecutors and judges.
This doctoral project will be conducted within the framework of the sub-project oral statements. Within this sub-project, e.g. whether automated language analysis or human raters are best at determining whether someone is lying or telling the truth. This includes language technology and scenario-based experiments with e.g. police officers, prosecutors and judges. In addition to this, it is evaluated which features distinguish sincere and lying statements, as well as which signals human assessors use in practice. The doctoral project primarily aims at the parts that include language technology but also collaborations with other EB-CRIME researchers regarding the comparison with human assessors etc.
Deadline : October 4, 2024
(02) Fully Funded PhD Position
PhD position summary/title:– Doctoral student in stabilizing measures for power systems
Hydropower and nuclear power account for the majority of electricity production in Sweden, and people often think that it is “just” to release water or steam to get electrical energy. This is correct in principle, but at a detailed level it is actually a complicated interaction between the electric generator and the power system it is connected to.
Small oscillations (unwanted swings) in the turbine during operation can be amplified in the generator and cause the output to fluctuate significantly and can lead to mechanical damage. In order to avoid the phenomenon, models are needed that describe reality satisfactorily. Questions can then be asked of these models about how to reduce the swinging so that our electricity system becomes even more reliable of supply and electricity producers can avoid problems in their power stations.
The principle also applies to nuclear power plants and wind turbines, or to all types of power that have a turbine connected to a generator.
Possible solutions to the problem may involve measures in the power grids, or control of the turbine/generator in a technically challenging manner.
Take the chance to become one of Sweden’s experts on rotor angle commutation and electrical systems. Familiarize yourself with the electrical system and large electrical machines and their interaction. The project aims to build competence in Sweden for the so-called RFG issues (Requirements for Generators), an international regulatory framework that describes the requirements placed on electricity producers who want to connect to an overlying larger transmission network. Often there are questions about stability, so the need for people who know with insight how things work and can solve problems when problems arise, is great.
The PhD position is a collaboration between Uppsala University, VOITH Hydro AB and Vattenfall AB. The problems are solved in consensus and knowledge.
We are looking for a motivated person who wants to be part of a driven team of 7 people who work with the challenges of the future for electrical systems and electrical production facilities. The group consists of a good mix of doctoral students and senior people with varying skills and backgrounds. We value that we have different backgrounds and knowledge that we bring into the various projects.
Deadline : 31 October 2024
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(03) Fully Funded PhD Position
PhD position summary/title:– Doctoral student in nutrition science
In Sweden, the number of food poisonings is estimated to be half a million per year, but the dark figure is large. For vulnerable groups, food poisoning can be life-threatening, causing hospitalization and death, and there is no given control point that ensures consumers’ knowledge of food safety. International research shows that vulnerable risk groups may receive inconsistent, no or incorrect information about food safety from healthcare professionals. Inadequate knowledge of food safety reduces the ability to transmit accurate information. There is a research gap precisely when it comes to nursing staff’s knowledge, attitudes and behavior in relation to food safety. The project aims to study the ability to identify and communicate food safety in different professions who are responsible for food handling at different levels within, among other things, municipal care for the elderly. The data collection will focus on risk awareness, self-efficacy and goal fulfillment in relation to food safety and to be able to predict the factors behind knowledge about pathogens and risky foods, attitudes and food safe handling. Both quantitative and qualitative data collection methods will be applied.
Deadline : December 6, 2024
(04) Fully Funded PhD Position
PhD position summary/title:– PhD student in Materials Chemistry at the Program for Inorganic Chemistry
The PhD project involves research in the field of fundamental materials science studies of thin films of functional multicomponent materials, specifically focusing on growth using magnetron sputtering, thermoelectric properties and components, material growth of thin-film and low-dimensional materials, as well as supporting computational studies.
Deadline : 15 October 2024
(05) Fully Funded PhD Position
PhD position summary/title:– PhD student in Molecular Biology of Protein synthesis in Bacteria and Eukaryotes
The overall objective of the Sanyal lab is to investigate the molecular mechanisms underlying protein synthesis and protein folding to find solutions to the global antibiotic resistance problem in pathogenic bacteria, to reconstitute cellular transcription translation machinery in the test tube, to develop RNA based therapeutic tools and to study the evolution of the protein synthesis machinery. The Sanyal lab offers a stimulating multidisciplinary environment where cutting edge protein synthesis research is conducted using tools from biochemistry, biophysics, structural and molecular biology.
As part of the PhD study, the candidate will investigate the mechanisms regulating the protein synthesis machinery during dormancy and hibernation in bacteria and lower eukaryotes using rapid kinetics, FRET, and cryo-electron microscopy. The candidate will need to express, purify, and site-specifically label recombinant proteins with fluorescent probes. A major task will be to reconstruct a eukaryotic translation system in vitro using purified ribosomes, mRNA, tRNA, and translation factors. To elucidate the molecular mechanisms, the candidate will conduct kinetic experiments using stopped-flow and quench-flow techniques, and complement the results with cryo-EM in close collaboration with other members of the Sanyal lab.
Deadline : 7 October 2024
(06) Fully Funded PhD Position
PhD position summary/title:– PhD student in spatial biodiversity modeling
This position will be focused on developing and implementing new computational and statistical approaches for the purpose of modeling biodiversity. An emphasis will be on developing solutions with a high utility for decision makers and other stakeholders. This will require dialogue with public agencies, national and international conservation networks, and/or the private sector. A background or experience in any of these fields is an additional merit that will be of benefit for this position.
Deadline : 27 September 2024
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(07) Fully Funded PhD Position
PhD position summary/title:– PhD student in in Scientific Computing focusing on Energy-Efficient Algorithmic Solutions
With the rise of exascale computing and the explosion of data-intensive applications, the demand for faster, more energy-efficient algorithms has never been greater. Fundamental kernels and solvers—key components that power large-scale simulations and data analyses—can consume a significant portion of computational resources. While parallelization has traditionally been used to accelerate computations and tackle larger problems, it often compromises certain numerical properties, presenting a complex and exciting challenge: How can we retain accuracy while pushing the boundaries of performance?
The goal is to develop next-generation, energy-efficient algorithmic solutions tailored to data-intensive applications. You will work at the intersection of numerical analysis, computer arithmetic, and algorithm design to create methods that balance speed, accuracy, and energy consumption. Concretely, the work will focus on 1) reformulating key algorithms for greater efficiency, 2) leveraging state-of-the-art computer arithmetic tools to ensure numerical accuracy, and 3) developing practical solutions using mixed- and arbitrary-precision techniques that drive down energy usage in large-scale applications.
Deadline : 3 October 2024
(08) Fully Funded PhD Position
PhD position summary/title:– PhD student in Health Informatics
– A doctoral student will devote their time to graduate education mainly. The rest of the duties may involve teaching at the Department, including also some administration, to at most 20%.
– Conduct mixed-methods qualitative research to explore clinicians’ and patients’ experiences and opinions on the use of generative AI in healthcare.
– Independently design, execute, and analyze research studies, while also contributing to the collaborative efforts of the research team.
– Dedicated attendance at research and team meetings.
– Publish research findings in peer-reviewed journals and present them at national and international conferences.
– Engage with stakeholders, including clinicians, patients, AI developers and policymakers, to ensure the research is grounded in real-world applications and perspectives.
Contribute to the development of ethical guidelines and best practices for the integration of generative AI in clinical settings.
Deadline : 3 October 2024
(09) Fully Funded PhD Position
PhD position summary/title:– PhD student in in Machine Learning building on physical principles
There are two main strategies to derive and deduce models – either using theory-based first principles or data-driven approaches. This project aims to conduct basic research to create new tools for using these two modeling strategies in conjunction. Combining all prior knowledge, both in terms of available data and physical first principles, has the potential to result in better models than if we only had to rely on one of them. How physics should be combined with data-driven machine learning models depends on the problem and is an active and in many areas still underdeveloped research field.
By making machine learning models more physics-informed, they will also become more interpretable. This interpretability can transform these machine learning models from being black-box models into full-fledged scientific tools enabling new knowledge discoveries. Therefore, one aim of this project is to create machine learning models that not only can be leveraged by first principles, but in the future also can be used to enable new knowledge discoveries in the physical domains in which they are employed. Finally, the project also aims to use theories from physics to better understand why machine learning models are working, how they can be improved and quantify their fundamental limitations.
We have a strong connection with collaborators in physics and materials science at Uppsala University, with a growing interest in using machine learning methods to advance knowledge in their respective domains. These collaborations can enable relevant applications as part of the project.
The exact research topic is decided in a dialogue between the doctoral student and the supervisor. The position is funded by the Swedish Research Council.
Deadline : 18 October 2024
(10) Fully Funded PhD Position
PhD position summary/title:– PhD position in physics: neutron emission from fusion reactors
The goal of the PhD project is to further develop existing computer programs for calculating the expected neutron emission from a given fusion plasma (so-called synthetic diagnostics), as well as to integrate these synthetic diagnostics into the modelling framework being developed within FP3. Special focus will be on (i) implementing a more detailed calculation of the neutron emission resulting from elastic collisions between the energetic alpha particles formed in the fusion reactions and the thermal fuel ions (deuterium and tritium), (ii) validating the calculations against experimental data from JET, and (iii) using the refined computational tools to make more detailed predictions of the neutron emission at future fusion facilities, e.g. ITER and DEMO. These types of calculations form important input for the development and optimization of fusion neutron diagnostics and associated data analysis methods, which in turn play an important role for maximizing the delivered power in future fusion facilities. The work within the PhD project will take place in close collaboration with other researchers, mainly at Uppsala University, Chalmers and KTH, but also at foreign universities and research institutes.
The duties of a PhD student also include participation in postgraduate courses, amounting to 40 credits. The duties may also include participation in teaching and other departmental work, however max. 20% of working time. More information about the postgraduate program is available via this link.
Deadline : 2 October 2024
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(11) Fully Funded PhD Position
PhD position summary/title:– Doctoral (PhD) position in Nanotechnology and Functional materials, with focus on metal-organic frameworks (MOFs) for water harvesting and hydrogen generation
This is a project in the field of functional porous materials for applications such as gas separation (greenhouse gases), water harvesting, water purification, catalysis and drug delivery. Within the project there is expertise in the synthesis and optimization of a wide range of porous materials, including porous oxides, zeolites and metal-organic frameworks (MOFs), etc.
In this project, you are given the opportunity to focus on environmental applications of porous materials such as MOFs. Specific application areas include water harvesting by adsorption and catalytic hydrogen generation using MOFs. The project mainly involves the synthesis and characterization of existing and new MOFs, as well as the development of post-synthesis processing methods such as 3D printing and the construction of simple devices for water capture and hydrogen generation.
Deadline : 1 October 2024
(12) Fully Funded PhD Position
PhD position summary/title:– PhD in quantum information theory
We are looking for a highly motivated and ambitious PhD student in quantum information theory, focusing especially on quantum measurement theory and its applications.
Quantum measurement theory has various non-classical features, such as incompatibility and the unavoidable measurement backaction. Recent developments and the currently ongoing second quantum revolution have shown that quantum theory can be used in cutting-edge technological applications in, e.g., communication and metrology. These applications are fueled by correlations that are stronger than those producible classically. The purpose of the PhD project is to understand the role of quantum measurements in such correlations, and to extend this knowledge to attack problems in practical quantum information tasks. The PhD project belongs to the research group led by Roope Uola, which is part of the Wallenberg Initiative on Networks and Quantum Information. The position is officially with Uppsala University, but the student is expected to spend majority of their time at Nordita in Stockholm.
The doctoral appointment is time-limited to four years of full-time studies. Holders must primarily devote themselves to their own postgraduate education, i.e. research and course work. Other duties at the institution that relate to teaching and administrative work can be included in the framework of the employment (max. 20%), which extends the employment correspondingly.
Deadline : 30 September 2024
(13) Fully Funded PhD Position
PhD position summary/title:– Two PhD students in experimental hadron physics
We are looking for a PhD student who can participate in the collection and analysis of data from Belle II, as well as to develop modern analysis tools, possibly using machine-learning techniques, for electron-positron experiments. It is also possible to either include a theory component, or conduct a project within the hadron beam experiment HADES in Germany, if there is interest. The PhD student is expected to participate in meetings and workshops abroad work with simulations, reconstruction, analysis and interpretation of data, and contribute to tasks relevant for the operation and improvement of the experiment.
Deadline : 1 November 2024
(14) Fully Funded PhD Position
PhD position summary/title:– PhD position in Ionic Neuromorphic Devices and Circuits for next-generation computing
The human brain contains a vast number of neurons and synapses that enable unparalleled signal processing and computing functionalities. Inspired by this, neuromorphic computing (NC) mimics how the brain computes using electronic components. NC has thereby emerged as a promising technology for solving high-complexity puzzles efficiently. Nanopore/nanochannel-based ionic devices (iontronic devices), operating in an electrolyte environment, have recently emerged as competitive candidates for realising NC. They offer unique advantages, including abundant nonlinear mechanisms for mimicking neuromorphic behaviour, high biocompatibility, and low energy consumption.
In this PhD project, we will develop ionic neuromorphic devices and integrate them with traditional electronic device-based neuromorphic units to create small-scale functional modules. These circuits will emulate neural behaviour, aiming for low-power and high-efficiency computation. This project involves both experimental development/measurement and theoretical modelling/investigation. Therefore, it requires the candidate to have a solid background in physics, electronics, and mathematics, as well as strong practical experimental skills.
Deadline : 31 October 2024
(15) Fully Funded PhD Position
PhD position summary/title:– PhD student in Physics
The Department of Physics and Astronomy has close to 400 employees, of which 100 are PhD students, and our research and education covers a wide range of physical topics. We offer participation in nationally and internationally leading projects for researchers, as well as opportunities for industrial partnerships and various outreach activities. The Ion Physics group, within the Department of Physics and Astronomy, investigates advanced materials for applications in fusion energy, smart windows, hydrogen storage & nanoelectronics. The group uses beams of swift ions to perform analytical techniques, for detailed material characterization in addition to fundamental investigations of the interaction of ions in matter from biological, environmental and technological contexts. The correlation between the composition and other sample properties can then be used to improve material performance or to obtain new properties. A 5 MV tandem accelerator, a 350 kV high current ion implanter and a Low-Energy Ion Scattering System form the experimental platform.
We hereby declare a PhD student position to be open for application. The PhD-studies will focus on the investigation of the diffusion properties of volatile elements such as Xe, Kr, I and Cs, in a range of different nuclear-fuel types, under a range of thermal conditions. The core of the methodology, by which this will be achieved, is ion-implantation of the volatiles in unirradiated nuclear-fuel followed by elemental depth-profiling with ToF-ERDA (Time-of-Flight – Elastic Recoil Detection Analysis) recoil detection analysis. Fuel samples will then be annealed and the effect of the annealing assessed by additional depth profiling. These general procedures will be further supported by a range of other material categorisation techniques, which will provide correlated information on changes in the microstructure of the samples. This multidimensional analysis will be coupled with detailed computer modelling of the physics involved.
Deadline : 30 September 2024
(16) Fully Funded PhD Position
PhD position summary/title:– PhD student in Automatic Control focusing on robust statistical learning and system identification
In this project, the selected candidate will join us in conducting research in automatic control and statistical learning, developing data-driven methods to learn large-scale signals and systems from data. There will be a strong focus on developing robust methods with mathematical guarantees, focusing on dynamical, statistical, and optimization properties with potential applications to medicine. The exact details of the research project are decided in a dialogue between the doctoral student and the supervisor.
Deadline : 9 October 2024
About Uppsala University, Sweden –Official Website
Uppsala University is a research university in Uppsala, Sweden. Founded in 1477, it is the oldest university in Sweden and all of the Nordic countries still in operation. It has ranked among the world’s 100 best universities in several high-profile international rankings during recent years. The university uses “Gratiae veritas naturae” as its motto and embraces natural sciences.
The university rose to pronounced significance during the rise of Sweden as a great power at the end of the 16th century and was then given a relative financial stability with the large donation of King Gustavus Adolphus in the early 17th century. Uppsala also has an important historical place in Swedish national culture, identity and for the Swedish establishment: in historiography, literature, politics, and music. Many aspects of Swedish academic culture in general, such as the white student cap, originated in Uppsala. It shares some peculiarities, such as the student nation system, with Lund University and the University of Helsinki.
Uppsala belongs to the Coimbra Group of European universities and to the Guild of European Research-Intensive Universities. The university has nine faculties distributed over three “disciplinary domains”. It has about 44,000 registered students and 2,300 doctoral students. It has a teaching staff of roughly 1,800 (part-time and full-time) out of a total of 6,900 employees. Twenty-eight per cent of the 716 professors at the university are women. Of its turnover of SEK 6.6 billion (approx. USD 775 million) in 2016, 29% was spent on education at Bachelor’s and Master’s level, while 70% was spent on research and research programs.
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